
For the past three years, "Meta" and "Ray-Ban" have been synonymous in the smart glasses space. Not anymore. Yesterday, I slipped on several pairs of Meta Glasses - no Ray-Bans - in three different styles and seven colors. One style, I was told several times by various enthusiastic Meta spokespeople, is a collaboration with socialite and reality TV star Kylie Jenner. Meta could've struck out on its own from the get-go, but teaming up with EssilorLuxottica and the Ray-Ban brand
Meta has launched smart glasses under its own brand name, without the Ray-Ban partnership that defined its previous models, and the new glasses cost $80 less than previous versions. The new glasses come in three styles and multiple colors, including a collaboration with a socialite and reality TV star. Meta's previous partnership with Ray-Ban was valuable because Ray-Ban's established name and iconic designs made the smart glasses look like ordinary eyewear rather than unfamiliar tech gadgets. However, Meta faces a significant challenge with its smart glasses brand due to the company's history of privacy scandals, and recent reports indicate Meta is developing a facial recognition feature for the glasses.

The all-cash deal gives MoEngage access to technology that assigns AI agents to individual customers.

A new update for Google Home could make it less likely your smart home cameras mistake you for someone else, just because you're facing away from the camera. Starting June 23rd, Google's expanding its facial recognition feature so that people you've tagged in your Familiar Faces library can continue to be identified when their faces aren't clearly visible, using "additional non-biometric signals (body size, clothing color, etc.)." The Familiar Faces library will also begin aut

In this tutorial, we build a speech recognition and translation workflow using NVIDIA Canary-1B-v2. We begin by setting up the required audio, NeMo, NumPy, and SciPy dependencies, then load the Canary model on a GPU-enabled runtime for efficient inference. From there, we prepare audio into a clean 16 kHz mono format, perform English ASR, translate speech into multiple languages, generate word and segment timestamps, export translated subtitles as an SRT file, test long-form transcription, run b
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